{"title":"Deep learning and generative artificial intelligence methods in enzyme and cell engineering","authors":"Steffen Docter , Benoit David , Holger Gohlke","doi":"10.1016/j.copbio.2025.103393","DOIUrl":null,"url":null,"abstract":"<div><div>Efficient enzymes and microbial factories are essential to promote the transition toward a sustainable bioeconomy. This review focuses on the progress of artificial intelligence (AI) methods in accelerating the development of optimized biocatalysts and genetic networks in cells. Recent advances in AI in the field of enzyme discovery, engineering, and <em>de novo</em> design are discussed. Additionally, we highlight examples of successful applications of AI in optimizing different components in cells, from gene expression regulation to metabolic pathway optimization and design. Finally, this review emphasizes the challenges limiting the reliability and generalizability of current AI methods.</div></div>","PeriodicalId":10833,"journal":{"name":"Current opinion in biotechnology","volume":"97 ","pages":"Article 103393"},"PeriodicalIF":7.8000,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in biotechnology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0958166925001375","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/12/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Efficient enzymes and microbial factories are essential to promote the transition toward a sustainable bioeconomy. This review focuses on the progress of artificial intelligence (AI) methods in accelerating the development of optimized biocatalysts and genetic networks in cells. Recent advances in AI in the field of enzyme discovery, engineering, and de novo design are discussed. Additionally, we highlight examples of successful applications of AI in optimizing different components in cells, from gene expression regulation to metabolic pathway optimization and design. Finally, this review emphasizes the challenges limiting the reliability and generalizability of current AI methods.
期刊介绍:
Current Opinion in Biotechnology (COBIOT) is renowned for publishing authoritative, comprehensive, and systematic reviews. By offering clear and readable syntheses of current advances in biotechnology, COBIOT assists specialists in staying updated on the latest developments in the field. Expert authors annotate the most noteworthy papers from the vast array of information available today, providing readers with valuable insights and saving them time.
As part of the Current Opinion and Research (CO+RE) suite of journals, COBIOT is accompanied by the open-access primary research journal, Current Research in Biotechnology (CRBIOT). Leveraging the editorial excellence, high impact, and global reach of the Current Opinion legacy, CO+RE journals ensure they are widely read resources integral to scientists' workflows.
COBIOT is organized into themed sections, each reviewed once a year. These themes cover various areas of biotechnology, including analytical biotechnology, plant biotechnology, food biotechnology, energy biotechnology, environmental biotechnology, systems biology, nanobiotechnology, tissue, cell, and pathway engineering, chemical biotechnology, and pharmaceutical biotechnology.